Open Access

ARTICLE

A Hybrid Mashup Platform Based on Structured and Unstructured Peer-to-Peer Networks Empowered with Genetic Algorithms

Osama Al-Haj Hassan^1,*, Ammar Odeh¹, Abdullah Aref ², Ghassan Samara³

1 Department of Computer Science, Princess Sumaya University for Technology, Amman, Jordan
2 Department of Data Science, Princess Sumaya University for Technology, Amman, Jordan
3 Department of Computer Science, Zarqa University, Zarqa, Jordan

* Corresponding Author: Osama Al-Haj Hassan. Email:

Computers, Materials & Continua 2026, 88(3), 56 https://doi.org/10.32604/cmc.2026.083861

Received 13 April 2026; Accepted 28 May 2026; Issue published 23 July 2026

Abstract

Mashups are among the key web technologies that provide end-users with customizable and personalized tools. Most mashup platforms are based on centralized architectures or do not employ fully decentralized architectures; therefore, in this paper, we propose a decentralized architecture for mashups that combines the strengths of structured and unstructured peer-to-peer networks. For the structured part, we rely on the Chord lookup protocol, and for the unstructured part, we build groups of nodes via two flavors of network flooding, namely, sequence number flooding and reverse path flooding. Brokers in the unstructured part would be responsible for hosting and executing mashups, such that deciding which brokers should host a given mashup is determined by utilizing genetic algorithms. We compare our work against several approaches that rely on random and greedy mashup placement. We also assess our proposed approach to pure structured and pure unstructured approaches. We evaluate our system using simulations, and results show that executing mashups using the version of our scheme that relies on reverse path flooding generates at least 25% lower delays than the other approaches.

---

Keywords

---